b1110
Challenges for the Singapore Economy
Nonetheless, whether monetary policy should be used as a tool
for limiting upswings in asset prices in Singapore still depends
empirically on the effectiveness of such policy in offsetting asset
price movements and, if the answer is yes, what the costs would be if
the bubble is deflated at the expense of slower economic growth
and higher unemployment. Moreover, since it is the mission of
MAS to promote sustained non-inflationary economic growth, it is
also important to understand the effects of asset price inflation on
consumer price inflation over the medium to long term.
In order to answer these questions empirically Chow and Choy
(2009) examined Singapore’s monetary system with particular refer-
ence to local stock price and house price cycles.
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GDP and the
consumer price index are used to represent domestic economic activ-
ity and price movements, while the Singapore residential property
price index and the Stock Exchange of Singapore (SES) price index
are used to proxy asset prices in the economy. For the reasons given
earlier, the TWS$ exchange rate is also included because Singapore is
a very small and open economy but, more importantly, because
changes in the TWS$ are a key indicator of the monetary policy
stance in Singapore. Interest rates and monetary aggregates, on the
other hand, are not included since the MAS does not explicitly target
these variables when it carries out monetary policy.
The time paths of the variables in the model following a one time
shock to monetary policy are then traced out and provide an indicator
of the extent to which monetary policy might influence asset prices. At
the same time, the responses of inflation and output growth serve as
an indication of both the benefits and costs of monetary policy.
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C. H. Kwan and P. Wilson
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They utilize a factor augmented VAR (FAVAR) model. The VAR model is a
dynamic system of equations that allows for interactions between economic variables
while imposing minimal assumptions about the underlying structure of the economy
while FAVAR models permit the incorporation of information from large datasets in
a parsimonious manner in order to adequately capture the information monitored by
the central bank for a better identification of monetary policy innovations. The mon-
etary VAR is augmented in this case with common factors extracted from a large
panel dataset spanning 127 local and foreign economic time series from the first
quarter of 1980 to the second quarter of 2008.
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